III:Small: Commugrate -- A Community-based Data Integration System

III:Small: Communigrate——基于社区的数据集成系统

• 批准号: 0916614
• 负责人: Walid Aref
• 金额: $ 49.84万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916614&HistoricalAwards=false
• 关键词: III; Small; Commugrate; Community; based

The goal of this project is to build Commugrate, a community-driven data integration system that capitalizes on the information gainedfrom the interactions of communities of humans with data sources.Commugrate tackles key challenges raised by the increase in thenumber of information sources used in science, engineering, andindustry, as well as the need for large-scale data integrationsolutions to enable effective access to these sources. These challengesinclude schema matching and mapping, record-linkage, and data repair.More specifically, Commugrate (i) utilizes both direct and indirectcontributions from different types of human communities with a focus onthe latter contributions, (ii) solves key data integration issues using new evidences like usage and behavior data which have not been previously used, (iii) adopts a new technique for schema matching, which defines a new class of its own, namely usage-based schema matching, (iv) introduces the first of its genre technique for record linkage based on entities' behavior, and (v) provides an adaptive feedback system to improve the quality of the data by making the best use of users feedback. Commugrate has a broad impact across multiple segments of society as data integration is by far the most important and in the same time vexing issue in many areas in sciences, engineering, and industry. Furthermore, leveraging users' interactions with data sources, especially indirect interaction, may provide several benefits and help solve many intractable data integration tasks which cannot be done without human intervention. PhD students will pursue research in this project. Publications, technical reports, software and experimental data from this research will be disseminated via the project web site at http://www.purdue.edu/cybercenter/commugrate.

该项目的目标是构建一个社区驱动的数据集成系统commgrate，该系统利用从人类社区与数据源的交互中获得的信息。commgrate解决了科学、工程和工业中使用的信息源数量增加所带来的关键挑战，以及对大规模数据集成解决方案的需求，以实现对这些信息源的有效访问。这些挑战包括模式匹配和映射、记录链接和数据修复。更具体地说，commgrate (i)利用了不同类型的人类社区的直接和间接贡献，重点关注后者的贡献；（ii）使用以前没有使用过的新证据，如使用和行为数据，解决了关键的数据集成问题；（iii）采用了一种新的模式匹配技术，该技术定义了一个新的类，即基于使用的模式匹配。（iv）引入了基于实体行为的记录链接的首个类型技术，(v)提供了一个自适应反馈系统，通过充分利用用户反馈来提高数据质量。由于数据集成是迄今为止在科学、工程和工业的许多领域中最重要、同时也是最棘手的问题，所以commgrate对社会的多个领域产生了广泛的影响。此外，利用用户与数据源的交互，特别是间接交互，可以提供一些好处，并有助于解决许多难以处理的数据集成任务，这些任务如果没有人工干预就无法完成。博士生将在这个项目中进行研究。本研究的出版物、技术报告、软件和实验数据将通过项目网站http://www.purdue.edu/cybercenter/commugrate发布。